NDLI: Hybrid PUSH-PULL for Data Diffusion in Sensor Networks without Location Information

Content Provider	IEEE Xplore Digital Library
Author	Xu Cheng Feng Wang Jiangchuan Liu
Copyright Year	2008
Description	Author affiliation: Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC (Xu Cheng; Feng Wang; Jiangchuan Liu)
Abstract	PUSH and PULL are two common data dissemination algorithms for data-centric sensor networks. The two algorithms work well with only a few sources or a few sinks, respectively; however, when there are many sources and many sinks, both of them become inefficient. In this paper, we propose a novel location-oblivious hybrid PUSH-PULL data diffusion (LOHD) algorithm, which suits a wide range of networks and source/sink settings. Different from existing hybrid approaches, LOHD does not rely on any location information; it adaptively selects an ultra-node through a well-controlled flooding and the ultra-node maintains the gradients from sources to sinks. It then incorporates enhanced PUSH and PULL to distribute messages along the gradients instead of flooding. We model and analyze the algorithms and perform extensive simulations. The results show that LOHD remarkably outperforms both PUSH and PULL, particularly when the number of sources and sinks increases. We also show that the overhead well resists to such increase, suggesting LOHD is highly scalable.
Starting Page	2702
Ending Page	2706
File Size	276208
Page Count	5
File Format	PDF
ISBN	9781424420759
DOI	10.1109/ICC.2008.510
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Floods Analytical models Performance analysis Algorithm design and analysis Wireless sensor networks Telecommunication traffic Sensor phenomena and characterization Proposals Communications Society Computer networks
Content Type	Text
Resource Type	Article

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